api integration

app.py

@@ -1,45 +1,27 @@
 import argparse
-import torch
-from transformers import pipeline
-from interpreter import interpreter
+import os
+import requests
+from dotenv import load_dotenv
 
-# Load the model
-generator = pipeline("text-generation", model="gpt-neo-2.7B")
+load_dotenv()  # Load environment variables from .env
 
-# Define a function to handle input and generate text
 def generate_text(prompt):
-    return generator(prompt, max_length=100, do_sample=True)[0]["generated_text"]
+    url = "https://api-inference.huggingface.co/models/drogba771/EleutherAI/gpt-j-6B"  # Replace with your actual model URL
+    headers = {"Authorization": f"Bearer {os.getenv('HF_TOKEN')}"}
+    response = requests.post(url, headers=headers, json={"inputs": prompt})
+    if response.status_code == 200:
+        return response.json()[0]["generated_text"]
+    else:
+        return f"Error: {response.status_code} - {response.text}"
 
-# Define a function to handle input using OpenInterpreter
-def generate_interpreter_response(prompt):
-    return interpreter.chat(prompt)
-
-# CLI interface using argparse
 def cli_interface():
-    parser = argparse.ArgumentParser(description="Command-line interaction with the text generation model and OpenInterpreter.")
+    parser = argparse.ArgumentParser(description="Command-line interaction with the deployed model.")
     parser.add_argument("--task", type=str, help="The prompt or command to generate text for")
     args = parser.parse_args()
 
-    # Provide a default task if none is provided
     task = args.task if args.task else "Tell me a joke"
-
-    # Generate and print the result
     result = generate_text(task)
     print(result)
 
-    # Process task using OpenInterpreter
-    response = generate_interpreter_response(task)
-    print("OpenInterpreter Response:", response)
-
 if __name__ == "__main__":
     cli_interface()
-
-# Additional information about the OpenInterpreter project
-# OpenInterpreter allows LLMs to execute code (including Python, JavaScript, Shell commands, and more) in a local environment.
-# It provides a natural-language interface to your computer's general-purpose capabilities, such as creating and editing files,
-# controlling a web browser, and analyzing large datasets.
-# To get started, install OpenInterpreter using:
-# pip install open-interpreter
-# After installation, start the interpreter with the command:
-# $ interpreter
-# For more information, visit: https://github.com/OpenInterpreter

requirements.txt

@@ -1,3 +1,4 @@
-gradio==4.44.1
-open-interpreter
+transformers
 torch
+python-dotenv
+requests